Robotics & Machine Learning Daily News2024,Issue(Jun.24) :61-62.

Researchers at Colorado State University Publish New Data on Machine Learning (W arm-Season Microwave Integrated Retrieval System Precipitation Improvement Using Machine Learning Methods)

科罗拉多州立大学的研究人员发表了关于机器学习的新数据(W ARM-SEARM微波综合检索系统使用机器学习方法改善降水)

Robotics & Machine Learning Daily News2024,Issue(Jun.24) :61-62.

Researchers at Colorado State University Publish New Data on Machine Learning (W arm-Season Microwave Integrated Retrieval System Precipitation Improvement Using Machine Learning Methods)

科罗拉多州立大学的研究人员发表了关于机器学习的新数据(W ARM-SEARM微波综合检索系统使用机器学习方法改善降水)

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摘要

由一名新闻记者-机器人与机器学习每日新闻编辑-研究人员详细介绍了人工智能的新数据。根据NewsRx编辑在科罗拉多州科林斯堡的新闻报道,研究表明,“这项研究比较了2022年和2023年WA RM季节关于降水气候学的五个被筛选的机器学习模型的性能,输入特征包括基于N OAA-20 ATMS数据的微波综合检索系统(MiRS)的ret rieved产品。”这项研究的资助者包括Noaa;大气层合作研究所;科罗拉多州立大学;卫星和地球系统研究合作研究所;马里兰大学和/或地球系统科学跨学科中心。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting out of Fort Collins, Colorado, by NewsRx editors, research stated, "This study compares the performance of five se lected machine learning models regarding precipitation climatology during the wa rm season in 2022 and 2023 over the continental U.S. Input features included ret rieved products from the microwave integrated retrieval system (MiRS) based on N OAA-20 ATMS data." Funders for this research include Noaa; Cooperative Institute For Research in Th e Atmosphere; Colorado State University; Cooperative Institute For Satellite And Earth System Studies; University of Maryland/, earth System Science Interdiscipl inary Center.

Key words

Colorado State University/Fort Collins/Colorado/United States/North and Central America/Cyborgs/Emerging Technolog ies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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